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Category: robotics/AI – Page 2

Statistical mechanics method helps machines better understand complex systems

A study by University of Hawaiʻi researchers is advancing how we learn the laws that govern complex systems—from predator-prey relationships to traffic patterns in cities to how populations grow and shift—using artificial intelligence (AI) and physics.

The research, published in Physical Review Research, introduces a new method based on to improve the discovery of equations directly from noisy real-world data. Statistical mechanics is a branch of physics that explains how collective behavior emerges from individual particles, such as how the random motion of gas molecules leads to predictable changes in pressure and temperature.

In this new work, statistical mechanics is used to understand how different mathematical models “compete” when trying to explain a system. This matters because many scientific fields rely on understanding how systems change over time, whether tracking disease spread, analyzing or predicting the stock market. But real-world data is often messy, and traditional AI models can be unreliable when the data gets noisy or incomplete.

Family and peer conflicts predict teenage mental health issues, study finds

Identifying the factors that contribute to psychopathology and increase the risk of experiencing specific mental health conditions is a long-standing goal for many psychology researchers. While past studies have highlighted the crucial role of some experiences, particularly challenging events unfolding during childhood and adolescence, in the development of mental health disorders, their influence is often difficult to quantify and differentiate from other factors that could contribute to psychopathology.

Recent technological advances, particularly the development of increasingly sophisticated and computational analysis tools, have opened new possibilities for the study of disorders and their underlying patterns. When used to analyze the large amounts of data collected by and professionals over the past decades, these methods could help to uncover correlations between specific variables and hidden trends that are associated with psychopathology.

Researchers at Washington University in St. Louis and Washington University School of Medicine recently set out to explore the possible contribution of different factors to poor mental health among teenagers using data mining techniques (i.e., computational approaches to uncover patterns in data). Their findings, published in Nature Mental Health, suggest that , particularly conflicts between , bullying or a loss of reputation among peers, are the strongest predictors of psychopathology in adolescents.

A flexible lens controlled by light-activated artificial muscles promises to let soft machines see

Inspired by the human eye, our biomedical engineering lab at Georgia Tech has designed an adaptive lens made of soft, light-responsive, tissuelike materials. Our study is published in the journal Science Robotics.

Adjustable camera systems usually require a set of bulky, moving, solid lenses and a pupil in front of a camera chip to adjust focus and intensity. In contrast, human eyes perform these same functions using soft, flexible tissues in a highly compact form.

Our lens, called the photo-responsive hydrogel soft lens, or PHySL, replaces rigid components with soft polymers acting as artificial muscles. The polymers are composed of a hydrogel —a water-based polymer material. This hydrogel muscle changes the shape of a soft lens to alter the lens’s focal length, a mechanism analogous to the ciliary muscles in the human eye.

AI-guided drones use 3D printing to build structures in hard-to-reach places

Disaster has just struck, roads are inaccessible, and people need shelter now. Rather than wait days for a rescue team, a fleet of AI-guided drones takes flight carrying materials and the ability to build shelters, reinforce infrastructure, and construct bridges to reconnect people with safety.

It sounds like , but new research from Carnegie Mellon University’s College of Engineering combines drones, additive manufacturing, and to rethink the future of aerial construction.

Aerial (AM)—think flying 3D printers, has been fascinating researchers for years, but the natural instability of a drone in flight makes traditional layer-by-layer fabrication nearly impossible. To overcome this, Amir Barati Farimani, associate professor of mechanical engineering, has equipped drones with magnetic blocks to allow for precise pick-and-place assembly and a large language model (LLM) that can translate high-level design goals like “build a bridge” into executable plans.

Rocket maker Firefly Aerospace files to go public under ticker FLY

Rocket maker Firefly Aerospace filed for an initial public offering on Friday, with plans to trade under the ticker symbol “FLY” on the Nasdaq.

Firefly’s planned offering comes during a resurgence period for IPOs after the market collapsed in 2022 as rising interest rates and skyrocketing inflation deterred investors from betting on riskier assets.

Some companies, including Klarna and ticket reseller StubHub, delayed public offerings earlier this year as President Donald Trump’s tariff plans rattled global markets. But venture capitalists are becoming more optimistic after a strong June for deal activity that included a surge in crypto company Circle and a major Meta Platforms deal with Scale AI. Figma also filed its prospectus earlier this month.

Floating Robotics: Advanced Greenhouse Automation Solutions

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Discover Floating Robotics’ cutting-edge robotic systems designed to automate greenhouse tasks like harvesting and de-leafing, enhancing efficiency and sustainability in modern agriculture.

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